Relationship between mobility and road traffic injuries during COVID-19 pandemic—The role of attendant factors

Abstract

This study investigates the important role of attendant factors, such as road traffic victims’ access to trauma centres, the robustness of health infrastructure, and the responsiveness of police and emergency services in the incidence of Road Traffic Injuries (RTI) during the pandemic-induced COVID-19 lockdowns. The differential effects of the first and second waves of the pandemic concerning perceived health risk and legal restrictions provide us with a natural experiment that helps us differentiate between the impact of attendant factors and the standard relationship between mobility and Road Traffic Injuries. The authors use the auto-regressive recurrent neural network method on two population levels–Tamil Nadu (TN), a predominantly rural state, and Chennai, the most significant metropolitan city of the state, to draw causal inference through counterfactual predictions on daily counts of road traffic deaths and Road Traffic Injuries. During the first wave of the pandemic, which was less severe than the second wave, the traffic flow was correlated to Road Traffic Death/Road Traffic Injury. In the second wave’s partial and post lockdown phases, an unprecedented fall of over 70% in Road Traffic Injury—Grievous as against Road Traffic Injury—Minor was recorded. Attendant factors, such as the ability of the victim to approach relief centres, the capability of health and other allied infrastructures, transportation and medical treatment of road traffic crash victims, and minimal access to other emergency services, including police, assumed greater significance than overall traffic flow in the incidence of Road Traffic Injury in the more severe second wave. These findings highlight the significant role these attendant factors play in producing the discrepancy between the actual road traffic incident rate and the officially registered rate. Thus, our study enables practitioners to observe the mobility-adjusted actual incidence rate devoid of factors related to reporting and registration of accidents.

Resilience of hospital and allied infrastructure during pandemic and post pandemic periods for maternal health care of pregnant women and infants in Tamil Nadu, India ‐ A counterfactual analysis

“…Consequently, as Kandaswamy Paramasivan and colleagues reported, most roads were devoid of vehicles when the strict stay-at-home orders were in-force, consequently, road crashes declined phenomenally. Expectedly the trauma vehicle calls increased significantly during these periods [ 30 ]…”

“…Consequently, as Kandaswamy Paramasivan and colleagues reported, most roads were devoid of vehicles when the strict stay-at-home orders were in-force, consequently, road crashes declined phenomenally. Expectedly the trauma vehicle calls increased significantly during these periods [30] Ram & Sornette's study designed a framework to understand and quantify the effectiveness of the interventions implemented by various countries, including China, Italy, Spain, Switzerland, France, Canada, United States, Germany, India, and Japan, to control epidemic growth [31]. They evaluated the time evolution of effective reproduction numbers in various geographical regions and then estimated the counterfactual evolution of effective reproduction number to quantify the impact of various lockdown measures.…”

The impact of COVID-19 restrictions on motorcycle crashes in Taiwan

“…[1][2][3] For instance, societal lockdown aimed at reducing the transmission of COVID-19 has been shown to decrease traffic crashes leading to nonserious or no injuries, but not those resulting in severe injuries or deaths. [3][4][5][6][7][8] Motorcycle crashes are a leading contributor to hospitalization and may crowd out resources allocated for COVID-19. [9][10][11] Unlike most Western countries, motorcycles are the most popular means of transportation in Taiwan.…”

“…[1–3] For instance, societal lockdown aimed at reducing the transmission of COVID-19 has been shown to decrease traffic crashes leading to nonserious or no injuries, but not those resulting in severe injuries or deaths. [3–8]…”